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*** Replication code for "The 'Commitment trap' Revisited: ***
*** Experimental Evidence on Ambiguous Nuclear Threats" by ***
*** Michal Smetana, Marek Vranka, and Ondrej Rosendorf     ***
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*** The code was written in Stata 17.0 BE-Basic Edition ***

*** Please reach out to ondrej.rosendorf@fsv.cuni.cz if you have any questions concerning this replication file ***

*** IMPORTANT: This file is accompanied by the svr_jeps_replication_data2 dataset ***

*** Before proceeding with the replication, please make sure that the "coefplot" and "estout" package is installed ***

*** To install the coefplot package, use the following command ***

ssc install coefplot, replace

*** To install the estout package, use the following command ***

ssc install estout, replace

*** Setting the output scheme to black and white ***

set scheme s1mono

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*** Replication of the results in Appendix 11 ***
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*** Appendix 11, Figure 1 - Approval (DV), no subset ***

* Running the ordinal logit model (Model 1)
ologit approval_ordinal i.scenario_n

* Storing the estimates (Model 1)
estimates store M1

* Running the ordinal logit model with controls (Model 2)
ologit approval_ordinal i.scenario_n i.male c.age c.income i.education_bin i.party

* Storing the estimates (Model 2)
estimates store M2

* Generating the coefficient plot (Appendix 11, Figure 1)
coefplot M1, bylabel(Model 1) || M2, bylabel (Model 2) ||, xline(0) coeflabels(1.scenario_n = "{bf:Treatment (NFU – Control)}" 1.male = "Gender (male)" age = "Age" income = "Income" 1.education_bin = "Education (university degree)" 1.party = "Party (Democrat – Republican)" 2.party = "Party (Independent – Republican)")

* Exporting the coefficient plot (Appendix 11, Figure 1)
graph export A11F01.png

*** Appendix 11, Table 1 - ordinal logistic regression (Model 1 and 2) ***

* Generating a table with results (Appendix 11, Table 1)
esttab M1 M2 using A11T01.rtf, noeqlines eqlabels(none) eform nogaps se pr2 varlabels(1.scenario_n "Treatment (NFU - control)" 1.male "Gender (male)" age "Age" income "Income" 1.education_bin "Education (university degree)" 1.party "Party (Democrat - Republican)" 2.party "Party (Independent - Republican)" _cons "Constant") drop(0.scenario_n 0.male 0.education_bin 0.party cut1 cut2 cut3 cut4 cut5 cut6) mtitle("Approval" "Approval") title(Table 1: Ordinal logistic regression of crisis handling approval) nonumbers mlabels("Model 1" "Model 2")

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*** Continue with svr_jeps_replication_code3 ***
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